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Authors were challenged with a task of developing a full vehicle simulation model, with a target to simulate the electrical system performance and perform digital tests like Battery Charge Balance, in addition to the fuel efficiency estimation. A vehicle is a complicated problem or domain to model, due to the complexities of subsystems. Even more difficult task is to have a control algorithm which controls the vehicle model with the required control signals to follow the test specification. Particularly, simulating the control of a vehicle with a manual transmission is complicated due to many associated control signals (Throttle, Brake and Clutch) and interruptions like gear changes. In this paper, the development of a full vehicle model aimed at the assessment of electrical system performance of the vehicle is discussed in brief.

Micro hybrid Systems are emerging as a promising solution to reduce the fuel consumption and greenhouse gas emissions in emerging markets, where the strict emission requirements are being enforced gradually. Micro hybrid Systems reduce the fuel consumption and greenhouse gas emissions in a conventional vehicle with 12 V electrical system, by optimizing the electrical energy generation, storage, and distribution, with functions like Intelligent Alternator Control, Engine Stop/Start, and Load Management. With the advent of Connected Car Systems, information about the vehicle is seamlessly provided to the customer not just through the Human Machine Interface systems within the vehicle, but to other mobile devices used by the customers.

Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS). IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities.

Micro Hybrid Systems are essentially first step towards the electrification of the powertrains. They are aimed at improving the fuel efficiency of the conventional gasoline and diesel power trains with conventional 12 V electrical system, and thus reduce the CO2 emissions as well. Various technologies like Engine Stop-Start, Intelligent Alternator Control, and Electrical Energy Management Systems are included in the bracket of micro hybrid systems. These system functions demand a totally different approach for managing the SLI battery, which is a total departure from the conventional approach. Particularly, the Alternator Shutdown function of Intelligent Alternator Control maintains a calibrated average level of State of Charge, which is typically around 80%, to ensure that the battery can accept more current, during the energy recuperation, which indirectly improves fuel economy.

With the current state of ever rising fuel prices and unavailability of affordable alternate technologies, significant research and development efforts have been invested in recent times towards improving fuel efficiency of vehicles powered with conventional internal combustion engines. To achieve this, a varied approach has been adopted by researchers to cover the entire energy chain including fuel quality, combustion quality, power generation efficiency, down-sizing, power consumption efficiency, etc. Apart from energy generation, distribution and consumption, another domain that has been subjected to significant scrutiny is energy recuperation or recovery. A moving vehicle and a running engine provide a number of opportunities for useful back-recovery and storage of energy. The most significant sources for recuperation are the kinetic energy of the moving vehicle or running engine and to a lesser extent the thermal energy from medium such as exhaust gas.